PointPillar Kitti training issue

My KITTI data folder is listed in 3 categories as per script:
data_object_calib
data_object_label_2
data_object_velodyne
```

import os
import sys
import open3d.ml as _ml3d
import open3d.ml.tf as ml3d

cfg_file = "/content/Desktop/point_pillars/Open3D-ML/ml3d/configs/pointpillars_kitti.yml"
cfg = _ml3d.utils.Config.load_from_file(cfg_file)

model = ml3d.models.PointPillars(**cfg.model) #ml3d.models.PointPillars(**cfg.model)

datapath = "/content/Desktop/KITTI_DATASET/KITTI_PTCLOUD_DATA/data_object_velodyne"

dataset = ml3d.datasets.KITTI(dataset_path=datapath, use_cache = True)

pipeline = ml3d.pipelines.ObjectDetection(model=model, dataset = dataset, **cfg.pipeline)

pipeline.run_train()
```

With KITTI yml file straight from master:

```
dataset:
name: KITTI
dataset_path: # path/to/your/dataset
cache_dir: ./logs/cache
steps_per_epoch_train: 5000

model:
name: PointPillars
ckpt_path: # path/to/your/checkpoint

batcher: "ignore"

point_cloud_range: [0, -39.68, -3, 69.12, 39.68, 1]
classes: ['Pedestrian', 'Cyclist', 'Car']

loss:
focal:
gamma: 2.0
alpha: 0.25
loss_weight: 1.0
smooth_l1:
beta: 0.11
loss_weight: 2.0
cross_entropy:
loss_weight: 0.2

voxelize:
max_num_points: 32
voxel_size: &vsize
[0.16, 0.16, 4]
max_voxels: [16000, 40000]

voxel_encoder:
in_channels: 4
feat_channels: [64]
voxel_size: *vsize

scatter:
in_channels: 64
output_shape: [496, 432]

backbone:
in_channels: 64
out_channels: [64, 128, 256]
layer_nums: [3, 5, 5]
layer_strides: [2, 2, 2]

neck:
in_channels: [64, 128, 256]
out_channels: [128, 128, 128]
upsample_strides: [1, 2, 4]
use_conv_for_no_stride: false

head:
in_channels: 384
feat_channels: 384
nms_pre: 100
score_thr: 0.1
ranges: [
[0, -39.68, -0.6, 70.4, 39.68, -0.6],
[0, -39.68, -0.6, 70.4, 39.68, -0.6],
[0, -39.68, -1.78, 70.4, 39.68, -1.78]
]
sizes: [[0.6, 0.8, 1.73], [0.6, 1.76, 1.73], [1.6, 3.9, 1.56]]
rotations: [0, 1.57]
iou_thr: [[0.35, 0.5], [0.35, 0.5], [0.45, 0.6]]

augment:
PointShuffle: True
ObjectRangeFilter:
point_cloud_range: [0, -39.68, -3, 69.12, 39.68, 1]
ObjectSample:
min_points_dict:
Car: 5
Pedestrian: 10
Cyclist: 10
sample_dict:
Car: 15
Pedestrian: 10
Cyclist: 10

pipeline:
name: ObjectDetection
test_compute_metric: true
batch_size: 6
val_batch_size: 1
test_batch_size: 1
save_ckpt_freq: 5
max_epoch: 200
main_log_dir: ./logs
train_sum_dir: train_log
grad_clip_norm: 2

optimizer:
lr: 0.001
betas: [0.95, 0.99]
weight_decay: 0.01

# evaluation properties
overlaps: [0.5, 0.5, 0.7]
similar_classes: {
Van: Car,
Person_sitting: Pedestrian
}
difficulties: [0, 1, 2]
summary:
record_for: []
max_pts:
use_reference: false
max_outputs: 1

```

Currently errors out in training (found the ptclouds, but fails past 8 %):

>
> INFO - 2022-01-10 17:24:29,676 - object_detection - Logging in file : ./logs/PointPillars_KITTI_tf/log_train_2022-01-10_17:24:29.txt
> INFO - 2022-01-10 17:24:29,676 - kitti - Found **3712** pointclouds for training
> INFO - 2022-01-10 17:24:29,811 - object_detection - Restored from ./logs/PointPillars_KITTI_tf/checkpoint/ckpt-30
> INFO - 2022-01-10 17:24:29,812 - object_detection - Writing summary in train_log/00013_PointPillars_KITTI_tf.
> INFO - 2022-01-10 17:24:29,812 - object_detection - Started training
> INFO - 2022-01-10 17:24:29,812 - object_detection - === EPOCH 146/200 ===
> training: 0%| | 0/619 [00:00 2022-01-10 17:24:29.836870: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2400000000 Hz
> 2022-01-10 17:24:30.767434: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 266141696 exceeds 10% of free system memory.
> 2022-01-10 17:24:35.794663: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
> **training - loss_cls: 0.843 loss_bbox: 0.872 loss_dir: 0.172 > loss: 1.888: 8%| | 49/619 [14:37<2:42022-01-10 17:39:07.528121**: W tensorflow/core/framework/op_kernel.cc:1755] Unknown: **InvalidArgumentError: ConcatOp : Ranks of all input tensors should match: shape[0] = [2,7] vs. shape[4] = [0] [Op:ConcatV2] name: concat**

The invalid argument seems to be coming from:

> File "/content/Desktop/point_pillars/env/lib/python3.8/site-packages/tensorflow/python/data/ops/dataset_ops.py", line 961, in generator_py_func
> values = next(generator_state.get_iterator(iterator_id))
>
> File "/content/Desktop/point_pillars/Open3D-ML/ml3d/tf/models/point_pillars.py", line 341, in batcher
> bboxes = tf.concat([

GIven that I'm running straight master with no modification + using given KITTI data + default kitti.yaml script, some help is greatly appreciated.

Thanks!